def colorRamp(num_points, colorRamp, code):
colorTable = pd.read_csv("color/color.csv")
idx_df = colorTable.set_index(["NAME"])
[startColor, endColor] = ms.parseStr(colorRamp, "-")
rgb_start = [int(idx_df.loc[startColor, "R"]),
int(idx_df.loc[startColor, "G"]),
int(idx_df.loc[startColor, "B"])]
rgb_end = [int(idx_df.loc[endColor, "R"]),
int(idx_df.loc[endColor, "G"]),
int(idx_df.loc[endColor, "B"])]
# [R_list, G_list, B_list]
rgb_list = [ar.interp(s, e, num_points)
for (s, e) in zip(rgb_start, rgb_end)]
if code == "hex":
hex_list = []
for i in range(num_points):
r = rgb_list[0][i]
g = rgb_list[1][i]
b = rgb_list[2][i]
string = rgb2hex(r, g, b)
hex_list.append(string)
return hex_list
elif code == "rgb":
color_list = []
for i in range(num_points):
r = int(rgb_list[0][i])
g = int(rgb_list[1][i])
b = int(rgb_list[2][i])
color_list.append([r, g, b])
return color_list
def breakpt(data, num_category, method, wtnumpy):
minimaxi = od.findMinMax(data)
mini = minimaxi[0]
maxi = minimaxi[1]
# equal distance of data between max and min
if (method == "even"):
breakpoints = ar.interp(mini, maxi, num_category + 1)
# same number of data per group
elif (method == "quantile"):
interval = 1.0 / num_category * 100.0
# if you have the numpy package
if wtnumpy:
breakpoints = [np.percentile(data, interval * x)
for x in range(num_category)] + [maxi + 1]
else:
interval = 1.0 / num_category
breakpoints = [percentile(sorted(data), interval * x)
for x in range(num_category)] + [maxi + 1]
# implement later
elif (method == "Jenks"):
print("not implemented yet!")
# psudo code: Calculate the sum of squared deviations between
# classes (SDBC). Calculate the sum of squared deviations
# from the array mean (SDAM). Subtract the SDBC from the SDAM
# (SDAM-SDBC). This equals the sum of the squared deviations
# from the class means (SDCM). After inspecting each of the
# SDBC, a decision is made to move one unit from the class
# with the largest SDBC toward the class with the lowest SDBC.
return breakpoints
def colorInterp(num_points, rgb_start, rgb_end):
rgb_list = [ar.interp(s, e, num_points)
for (s, e) in zip(rgb_start, rgb_end)]
return [[rgb_list[0][i], rgb_list[1][i], rgb_list[2][i]] for i in
range(num_points)]